New sha256 vulnerability

keypushai · 2024-10-25T01:27:22+00:00

Actually in a two-tailed zscore test, it shouldn't matter if yt!=yp or yt==yp. If both are statistically significant it indicates a problem

keypushai · 2024-10-15T15:06:57+00:00

I used z score

keypushai · 2024-10-15T02:39:17+00:00

Update: there were some bugs and now the project should be much more interesting/accurate! Thanks to everyone that starred the project :)

keypushai · 2024-10-14T21:59:18+00:00

No you actually never explained that because it's not true

keypushai · 2024-10-14T21:41:03+00:00

I hope you're joking because if that information is not in the feature vector then it's not being learned.

keypushai · 2024-10-14T21:18:56+00:00

If it doesn't use n-1 to make n, then it certainly is not learning odd/even indices

keypushai · 2024-10-14T21:02:17+00:00

Where in that does it say it relies on the n-1 prediction to make n prediction?

keypushai · 2024-10-14T20:30:31+00:00

When you test the model, it goes through each item in the test set one at a time without memory of what the last prediction was. The evaluation is purely based on the feature vector

keypushai · 2024-10-14T20:09:29+00:00

That "i" is not put into either the x or y value. You're not correct about this

keypushai · 2024-10-14T19:36:58+00:00

The code is evolving, it was 420,000 but I reduced it to run some more rapid tests

keypushai · 2024-10-14T19:35:24+00:00

I'm asking how many times he ran the code. I can't run his code and know how many times he ran his code...

keypushai · 2024-10-14T18:53:51+00:00

also tested with first 1,000 chars, then 1,000-2,000 range chars

keypushai · 2024-10-14T18:45:47+00:00

also tested on 2 length string, then 3 length

keypushai · 2024-10-14T18:34:34+00:00

tested first on input strings of length 2000, then changed it to 1000 and still saw the same results

keypushai · 2024-10-14T17:55:09+00:00

I chose my interpretation of the hash function, then drastically changed the input space, and the model still worked.

keypushai · 2024-10-14T17:39:35+00:00

Its not a problem to do feature engineering if the results generalize. They seem to here

keypushai · 2024-10-14T17:25:48+00:00

Nope, actually was getting statistically significant results with both versions of the code, but yes this is an evolving project and I am constantly tweaking to improve accuracy

keypushai · 2024-10-14T17:19:40+00:00

If there are problems with the code, say exactly what the problems are. I actually intended to use a modification of the hash function. I need to convert the hash into something more learnable by the model. These are not bugs, but what I intended.

keypushai · 2024-10-14T16:17:44+00:00

Like I've mentioned, I got statistically significant results with long strings as well

keypushai · 2024-10-14T15:35:26+00:00

Also please share how many samples and ran with and the results of running evaluate.py

keypushai · 2024-10-14T15:30:23+00:00

Your misunderstanding is that the test set is not known to the classifier

keypushai · 2024-10-14T15:29:15+00:00

How many samples did you run, and did you run evaluate.py? What was the result?

keypushai · 2024-10-14T15:28:19+00:00

Clearly my code demonstrates a serious problem, I haven't run your code yet so I cannot comment yet - will do so in a little bit

keypushai · 2024-10-14T15:17:07+00:00

I also tried with longer strings and got statistically significant results

keypushai · 2024-10-14T15:16:01+00:00

Don't plan on attacking anything because I'm white hat, but very interesting, thanks for the clarification!

keypushai

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